PROBLEMS WE WORK ON
Making use of humanity’s vast collective knowledge is
hard, and the tools we have are not sufficient
Information is spread out and heterogeneous.
This makes it hard to access and make use of it.
Existing ways of managing information and software
require significant manual effort.
Many machine learning methods can not leverage our
understanding of the world which limits their
applications and robustness.
Our system strives to solve these problems. It aims to provide
services across different domains, acting as analysts,
personal assistants, data scientists, or scientific advisors.
METHODS WE USE
The goal we pursue is not easy. In order to tackle it, we need to be on the lookout for the most useful methods. In particular, our work heavily relies on these new and exciting scientific fields:
GOING BEYOND TODAY’S APPROACHES
Today, there are many approaches to AI,
each with their own strengths and weaknesses.
Rather than using them in isolation, we aim to create a system where they can be composed to get the best out of all, while avoiding their pitfalls.
Approach
Strengths
Weaknesses
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